Powered by OpenAIRE graph

High-Density Lipoprotein and Low-Density Lipoprotein Subfractions in Patients with Chronic Kidney Disease

Authors: Magdalena, Rysz-Gorzynska; Anna, Gluba-Brzozka; Maciej, Banach;

High-Density Lipoprotein and Low-Density Lipoprotein Subfractions in Patients with Chronic Kidney Disease

Abstract

Chronic Kidney Disease (CKD) is an independent risk factor for cardiovascular disease (CVD). CKD is accompanied by high cardiovascular mortality due to many factors, but atherosclerosis is thought to be a major cause at every CKD stage. It has been suggested that measuring and estimating changes in high density lipoprotein (HDL) and low density lipoprotein (LDL) subfractions may be important for predicting CVD in CKD patients.The aim of this study was to determine and compare levels of HDL and LDL subfractions in patients with different CKD stages.The study included 115 patients with CKD (CKD stage 2-25 patients, CKD stage 3-25; CKD stage 4-25 and CKD 5 undergoing dialysis - 40 patients) and 25 volunteers without CKD (control group). The Lipoprint System (Quantimetrix®) was used to analyse HDL and LDL subfractions.There were significant differences in the distribution of HDL1-HDL5 subfractions levels, which were significantly higher in patients with impaired renal function than in the control group (p≤.0.013 for all comparisons). HDL7-HDL10 subfractions were significantly more prevalent in healthy volunteers compared with CKD patients (p≤.0.001 for all comparisons). The analysis of LDL subfractions revealed significant differences only in IDL-B (p<0.05), IDL-A (p<0.05) and LDL2 (p<0.001) between patients with CKD stage 5 and controls.CKD influenced HDL and LDL subfractions. In CKD patients, large HDL subpopulations were more prevalent in contrast to small HDL subfractions in healthy subjects. Identification of patients with increased level of large HDL subfractions could be useful to identify CKD subjects at increased CV risk. Further studies with larger populations and with the application of a several methods of subfraction measurement are necessary to confirm these results.

Keywords

Male, Middle Aged, Risk Assessment, Severity of Illness Index, Lipoproteins, LDL, Cardiovascular Diseases, Renal Dialysis, Risk Factors, Case-Control Studies, Humans, Female, Renal Insufficiency, Chronic, Lipoproteins, HDL, Biomarkers, Aged

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    16
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%